Zuckerberg Says Facebook ‘Better Prepared’ for Election Meddling

Facebook is better prepared to defend against efforts to manipulate the platform to influence elections and has recently thwarted foreign influence campaigns targeting several countries, chief executive Mark Zuckerberg said Thursday.

Zuckerberg, posting on his Facebook page, outlined a series of steps the leading social network has taken to protect against misinformation and manipulation campaigns aimed at disrupting elections.

“We’ve found and taken down foreign influence campaigns from Russia and Iran attempting to interfere in the US, UK, Middle East, and elsewhere — as well as groups in Mexico and Brazil that have been active in their own country.”

Zuckerberg repeated his admission that Facebook was ill-prepared for the vast influence efforts on social media in the 2016 US election but added that “today, Facebook is better prepared for these kinds of attacks.”

But he also warned that the task is difficult because “we face sophisticated, well-funded adversaries. They won’t give up, and they will keep evolving.”

The Facebook co-founder said the social network remains in a constant battle with those who create fake accounts that could be used to spread false information — having blocked more than a billion.

“With advances in machine learning, we have now built systems that block millions of fake accounts every day,” he said.

“In total, we removed more than one billion fake accounts — the vast majority within minutes of being created and before they could do any harm — in the six months between October and March.”

Zuckerberg’s post was the latest in a series of steps aimed at repairing the damage from its missteps in 2016, including the hijacking of personal data on millions of Facebook users by a political consultancy working for Donald Trump.

Separately, Facebook announced it was expanding fact-checking for photos and videos to 27 partners in 17 countries around the world, up from 14 countries earlier this year.

“Similar to our work for articles, we have built a machine learning model that uses various engagement signals, including feedback from people on Facebook, to identify potentially false content,” said produce manager Antonia Woodford.

“We then send those photos and videos to fact-checkers for their review, or fact-checkers can surface content on their own.”